Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/6/2006
Publication Date: 6/15/2006
Citation: Chappell, A., Zobeck, T.M., Brunner, G. 2006. Using bi-directional soil spectral reflectance to model soilsurface changes induced by rainfall and wind-tunnell abrasion. Remote Sensing of Environment. 102(3-4):328-343.
Interpretive Summary: Computer models are available to predict wind erosion for locations of a variety of sizes, from fields to regional-sized areas. Methods to assess changes in soil surface properties are needed in order to improve and create better models. Remote sensing, observing surface properties from a distance, may provide a way to detect changes in soil surface properties affecting wind erosion without disturbing the surface and to do so for a wide variety of area sizes. In this study, we used a device that measures the reflectance of light wavelengths from the soil to compare three soils that were modified by applying artificial rainfall and then abrading the soils with sand in a wind tunnel. With the measurements of reflectance from the soil surface we were successful in identifying differences in soil texture (the relative amount of sand, silt and clay particles in the soil), the occurrence of a soil crust created by the artificial rainfall, and the presence of loose sand on the crust surface that could easily blow away. These results demonstrated that this type of remote sensing of the soil surface can be used to distinguish differences in soil surfaces caused by rainfall and wind erosion, without disturbing the soil surface. Since similar light reflectance measurement devices are carried on several of the earth-observing satellites currently in orbit, this research has potential for use in improving our understanding of soil properties and ultimately identifying and measuring erosion on a global scale.
Technical Abstract: To improve wind erosion model predictions over several spatial and temporal scales simultaneously, there is a requirement for a non-invasive approach that can be used to rapidly assess changes in the compositional and structural nature of a soil surface in time and space. Multi-angular spectral reflectance appears to provide a holistic framework for the measurement and prediction of soil surface characteristics remotely using ground-based radiometers and current and future generations of angular sensors on airborne and satellite platforms. To investigate the utility of this framework, a ground-based study was performed using three soils susceptible to wind erosion that were modified using rainfall simulation and wind tunnel abrasion experiments. Observations of those changes were made and recorded using digital images. Multi-angular spectral measurements of reflectance were also made and inverted against a bi-directional soil spectral reflectance model. Comparison of the measurements and predictions showed good agreement with small errors in accuracy. Optimised values of the model parameters produced the single scattering albedo and a description of the reflectance scattering behaviour of the soil surfaces that included an estimate of roughness. The model parameters removed the effect of the measurement conditions (illumination and viewing geometry) on the spectral reflectance. The combination of single scattering albedo spectra and model parameters for each treatment provided information about the composition and structure of the soil surface changes. The main changes detected at the soil surface included the presence of a crust produced by rainsplash, the production of loose erodible material covering a rain crust and the selective erosion of the soil surface. Variation in the soil surface reflectance was not explained solely by soil type. Instead, low intensity rainfall combined with short and long duration abrasion explained a significant portion. These findings provide a source of considerable variation in experimental and operational spectral reflectance measurements that has perhaps hitherto been largely ignored. The results demonstrated the readily available information on the composition and structure of the soil surface without interfering with natural processes.